The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
The amount of data generated by modern data centers and other computing environments is ever increasing. Many organizations are collecting increasing amounts of this generated data for subsequent analysis and other purposes. However, the usefulness of such collected data is often limited by users' ability to search and extract information relevant to a user's needs and as the amount of collected data grows, so too does the computational task of finding data relevant to a user's requests increases in difficulty.
One strategy for increasing the speed and accuracy with which information can be retrieved is to create an index. At a high level, an index maps a set of keys to particular values or locations within a collection of data at which the keys exist. In the context of computing environments, indexes may be used to increase the speed of search requests by mapping search keywords to locations in a set of data containing the keywords and/or by similarly indexing other values contained in the data. When a keyword-based search request is received, the index may be consulted to determine exactly where certain keywords are located instead of searching the entire set of data for the same information. However, as an amount of data stored by a computing device increases and as more of the data is indexed, an amount of storage used to store the indexes may grow to levels that significantly increase the cost of storage and operation.